Forecast visualisation

Forecasts of cases/deaths per week per 100,000. The date of the tab marks the date on which a forecast was made (only the latest forecasts and the previous 4 weeks shown).

2021-08-09

Cases

Deaths

2021-08-02

Cases

Deaths

2021-07-26

Cases

Deaths

2021-07-19

Cases

Deaths

Forecast calibration

The table and plot below show this week’s coverage of the ensemble model at the 50% and 95% level, across the 32 countries. This shows the proportion of observations that fall within a given prediction interval. Ideally, a forecast model would achieve 50% coverage of 0.50 (i.e., 50% of observations fall within the 50% prediction interval) and 95% coverage of 0.95 (i.e., 95% of observations fall within the 95% prediction interval). Values of coverage greater than these nominal values indicate that the forecasts are underconfident, i.e. prediction intervals tend to be too wide, whereas values of coverage smaller than these nominal values indicate that the ensemble forecasts are overconfident, i.e. prediction intervals tend to be too narrow.

Coverage (this week)

Coverage (over time)

The dashed line indicates the nominal 95% level and dotted line the 50% level. If the ensemble was perfectly calibrated, the corresponding coloured lines would coincide with these.

Cases

1 week

2 weeks

3 weeks

4 weeks

Deaths

1 week

2 weeks

3 weeks

4 weeks

PIT histograms

The figures below are PIT histograms for the most recent ensemble forecasts. These show the proportion of true values within each predictive quantile (width: 0.2). If the forecasts were perfectly calibrated, observations would fall evenly across these equally-spaced quantiles, i.e. the histograms would be flat.